Network Growth

Creating a Historical Database for Roads in Greater Sydney using Map Digitisation

| David Levinson

Recently published:

Abstract

The aim of this thesis is to create a historical database for roads in Greater Sydney using map digitisation. The database was constructed to label the status of road in Sydney at a certain time by nominating their opening date, and if applicable, their closing date. The project was completed in the QGIS working environment, an open-sourced program that allows for map digitisation to be completed. A method was developed for map digitisation that can be used to extract spatial data from historical maps and place them in a collective vector layer. The method considers extensive georeferencing of the maps, as well as editing and cleaning the maps through raster and vector analysis. Preferred methods for map digitisation used in the project were identified. For a considerable area of Sydney, in which approximately 52000 road links were included, almost half of the links were identified with an open date by the start of the twentieth century. A further half of these links were confined to opening within a thirty-year period. The progressive change in open links, the length of the network, the area of the network surveyed and the number of intersections open was also reviewed with time. The project has established a strong foundation for a historical road database for Sydney. It has also outlined methods and procedures that can be followed to progress the database further.

Growth of the Sydney Street network. Source: Turner, Hamish (2021)

Network Econometrics and the Evolution of Transport Systems

| David Levinson

Recently Published

Abstract

This thesis systematically develops a network correlation matrix that explicitly distinguishes competitive and complementary link pairs in transportation networks. Embedding the matrix in network econometric analysis, this thesis consolidates that incorporating representative spatial information with a network perspective is capable of improving the performance of traffic forecasting models. The method is validated in the context of a real-world transport system rather than within simulated settings adopted by previous research. An Autoregressive-Distributed Lag (ARDL) model is specified, and reveals that the combination of correlation strength and magnitude of lagged flow change on correlated links is an significant predictor of future traffic flow. This thesis innovatively extends network econometric methods, previously exclusively used for traffic flow forecasting, to the domain of network structure prediction by specifying a logit model. It finds that complementary and competitive links play distinct roles in shaping the network structure. If positively correlated, a link is more likely to undergo the same structural change influential links underwent previously where the influence is measured by a combination of correlation strength and link importance, reflected by historical flow level. Additionally, this thesis establishes a digitized database of the Sydney tramway system, providing a complete set of data for more research.

Trams running through Railway Square, 1920s

Evolution vs. Plans

| David Levinson

Evolution

Assuming we started with an undeveloped wilderness,  cities emerge at selected points (typically points with natural accessibility advantages over their neighbors, such as ports and harbors, or water falls, or railroad junctions). But they evolve from wilderness to city over time.

They do not generally evolve because someone built city-scale transportation out in the country and waited for the people to arrive.

Instead it is a ratchet: a few people, some transportation network investment; some more people, more investment; even more people, still more investment, and so on, until something resembling a city emerged.

While the infrastructure may slightly lead the development (as in the Streetcar Suburbs or London’s Underground) those developments in general contiguously extended the urban environment in appropriate steps, and were accompanied by development in the near term (failure to see development would have led to bankruptcy for the line).

Plans

Plans aim to take this chaotic, unpredictable, evolutionary process and put a sheen of order upon it.

The general problem with public sector transportation and land use plans is that they are static. They are made for one point in time. They are  snapshots in a world with 24 frames per second (for eternity), and for which we don’t know the ending (“no spoilers”).

Life-cycle of rail in the US. From The Transportation Experience, Figure 6-4
Life-cycle of rail in the US. From The Transportation Experience, Figure 6-4

 

They design for maturity and implicitly assume that the mature (built out) city sustains. The evidence from the life-cycle for every mode (or technology) is that its scope and extent are continuously changing.

The mirror of this problem is  they ignore the path that gets you there and all interim states, as well as changes in behavior and technology that may occur in the interim.

The third problem with plans is that they address future problems that don’t exist today, when there are plenty of problems today that remain unsolved. Trying to better manage how will people get around or from or to a site which might (or might not) transform from country to city, or even low density suburb to high density suburb, in 30 years when there are plenty of ways to help people get around better today is an exercise in pointlessness, whose primary objective is to transfer resources from the public to selected (and one presumes politically influential) landholders.

There is nothing wrong with having a vision. It presents a direction in which to proceed. The most important thing is the next step (or two) though. Each step you take in one direction is a step farther away from destinations in other directions. But the path on which we are walking is shrouded in smog. Our vision is simply our imagination (or consensual hallucination) of what lies down the road. We have never been there before. But we must recognize, we never will reach where we think we are going.

Path dependence

| David Levinson

If you don’t know where you’re going, any path will get you there.

Path dependence is the idea that where we are today depends critically on where we were yesterday. Some systems are path independent, those that have a single unique equilibrium. Finding the solutions to some math problems is independent of where you start, as long as you follow a particular algorithm.

However, most systems we deal with on a daily basis have some characteristics of path dependence. Where you live might depend on what job you took, which depends on what your previous job was and where you went to school, and a different decision anywhere along the way would change today’s position.

Nowhere is this more true than transportation. On the one hand, it is obvious that certain locations were destined to be important cities because of significant natural advantages. New York has a deep harbor at the confluence of major navigable river. Chicago is at the pivot point between vast agricultural lands to the Northwest and the shortest land path to the East Coast. It was natural railroads would flow through the point on the map we now call Chicago.

On the other hand, many city sites that were selected for natural advantages in one technological era (The Romans selected London and the Dutch and English chose New York in large part for their capability as ports), remain important even after that technology becomes obsolete. With the logistics revolution and the new dominance of container shipping, London’s shipping has moved northeast to Felixstowe as large container ships cannot easily ply the Thames, while New York’s shipping has migrated to the wide open spaces of New Jersey.

The one-time advantages result in a set of complementary investments and inter-related decisions that take on a life of their own. Because of local trading advantages, commodities markets, banks, insurers, and other related organizations located nearby. A critical mass of those institutions felt no need to migrate just because their initial raison d’être vanished. While a building is under construction, temporary framing will often be used until the more permanent structure is erected. Once the final building can stand on its own, the falsework is dismantled. In a sense, everything is falsework for what comes after.

This kind of mutual complementarity happens repeatedly in transportation. Airplanes are the perfect example of mobile capital. If Amalgamated Airlines no longer wants to serve a particular city pair, the airplane can easily be redeployed elsewhere. Yet 80 years into the commercial aviation industry, airlines today serve mostly the same hubs their predecessors did on the Airmail routes of the 1930s. American Airlines is still in Dallas, United in Chicago, Delta (Northwest) in Minneapolis, and so on.

While very few decisions are completely irreversible, transportation decisions come close. Where we place a right-of-way, or an airport will explain where that facility will be decades, or even centuries from now.

A slight deviation from the efficient path to solve a short term problem today will cost travelers time for years to come. It is important to get the design right for the long term. (Undoubtedly this has social costs, see e.g. I-94 through the Rondo in Saint Paul).

But a slight deviation from the path will also change what the long term is. Build a bridge “here” rather than “there”, and then you will adjust all of the roads feeding into the bridge to meet it “here” (instead of “there”). And then land will be developed along the road to “here” to take advantage of the newly created accessibility, properties will be platted, buildings will be built, travel and trade patterns established, and other critical dependencies will come to assume that the bridge is “here”. At some point, say 50 years in the future, the bridge will need to be replaced. Even if “there” was a better location than “here” initially, after five decades of adaptation, it is quite likely that “here” is better now. The whole may have been better were a different initial decision been made, given conditions at the time. Given current realities, that path must now be foregone.

In transportation we say build it right the first time, because there won’t be a second chance. And that is true. But also remember the world will adapt to whatever we do, and we cannot let the perfect be the enemy of the good.

ICA Workshop on Street Networks and Transport

| David Levinson

ICAheader

I am on the program committee for the ICA Workshop on Street Networks and Transport:

“Street networks, as one of the oldest infrastructure of transport in the world, play a significant role in modernization, sustainable development, and human daily activities in both ancient and modern times. Although street networks have been well studied in a variety of engineering and scientific disciplines including for instance transport, geography, urban planning, economics and even physics, our understanding of street networks in terms of their structure and dynamics is still very limited to deal with real world problems such as traffic jams, pollution, and human evacuations in case of disaster management. Thanks to the rapid development of geographic information science and related technologies, abundant data of street networks have been collected for better understanding the networks’ behavior, and human activities constrained by the networks. This ICA workshop is intended to gather researchers together to present the state of the art research and studies, in an interdisciplinary setting, on street networks and transport. Suggested topics include, but not limited to as long as they address issues related to street networks and/or transport:

  • Spatial statistics and spatial analysis along networks
  • Topological analysis and space syntax
  • Pattern recognition with street networks
  • Map generalization on street networks Complexity measurement of street networks
  • Human evacuations and simulations
  • Transport modeling based on street networks
  • Geospatial analysis of the OpenStreetMap data

Submission
All manuscripts in a length of 6000-7000 words should be in English, single column, single-spaced with figures and tables within the text. The manuscripts in MS Word 2003 format should contain authors’ affiliation and email, abstract (no longer than 200 words), and up to five keywords. To submit, please use EasyChair at http://www.easychair.org/conferences/?conf=icaworkshop2013
“

The structure and evolution of a skyway network

| David Levinson

skywayOverTime
Recently Published:

We study the structure and evolution of the downtown Minneapolis, Minnesota skyway network. Developed by private building-owners, the network evolved from tree-like to grid-like over the course of 50 years. We find that decentralized forces with the goal of maximizing individual buildings’ profitability shaped the network. Our analysis shows that a building with greater office size, a sign of greater accessibility, was more likely to be connected earlier. The distribution of existing skyway segments is found to follow a power-law function of the average degree, closeness, and eigenvector centralities of the vertices. We further explain and model the evolutionary process using an agent-based model. The simulation results suggest that the model replicates the network structure and its evolutionary process.

The Genius of Dirt Roads

| David Levinson

In City Journal, Brandon Fuller writes: The Genius of Dirt Roads :

“Angel writes that governments in the developing world, whose financial capacity is often limited, should focus on what may sound unglamorous: establishing an arterial grid of dirt roads throughout each city’s future territory, much as the commissioners did in Manhattan. The grid should connect to the city’s existing network of roads, of course, and it should cover an area that the city expects its future population growth to require. These arteries will one day carry public transportation and private traffic, and such infrastructure as water mains, sewers, storm drains, and telecommunications networks will follow their routes.”

The grid has advantages and drawbacks. In Planning for Place and Plexus we write:

The morphology and queuing properties of the plexus (its supply and demand) ultimately determine both the efficiency of the network in moving people and the efficiency of the land use. Radial (hub-and-spoke) networks allow easy access to the center but create inconvenient sharply angled parcels. In contrast, 90-degree grids maximize travel times (for anyone traveling in a diagonal direction) but create efficient parcels. A major issue with network topology is the interconnectedness of the network. Interconnected networks, be they grid or radial in nature, enable and even encourage through traffic, while a tree-like network discourages that problem. The topology of the network, grid, radial, organic (curvilinear) or otherwise, affects its performance.
The regular grid (with occasional interruptions) is arguably the most common topology for cities. It has been employed in cities for millennia. In the United States, the most influential legislation affecting the morphology of roads was the Land Ordinance of 1785. In many respects, it laid the foundation for future land use-transportation policy by adopting the Public Land Survey System, creating townships and subdividing them into 36 sections of one square mile (259 hectares) and 144 quarter-sections of 0.25 square mile (65 hectares) each. Roads delineating each of the sections were referred to as “section roads.” Subsequently, many urbanizing areas continued to use the centerlines of those roads as the location of present day arterials; the arterial networks are often further broken down into a finer grid of blocks.
A key point that has not been generally considered is the flexibility that the uniform and undifferentiated mesh networks (termed “grids” here) provide to changes in land use. A uniform grid allows alternative spacing between activities, spacing that can change with economies of scale. For instance, consider retailing. As described in Chapter 9, many stores—especially grocery stores—have been getting larger, while their numbers have dropped. Many New Urbanists, who advocate small-scale neighborhood retail, bemoan this phenomenon. Suppose that economies of scale indicate that it is efficient for the average retail store of a certain kind to increase in size from 1,000 to 2,000 ft2 (93 to 186 m2). Previously there may have been one such store every 10 blocks (one for every 100 square blocks); now there can be one every 14 blocks (one for every 200 square blocks). A grid allows the flexibility for re- spacing while keeping nearly optimal size stores. …
A tree network, in contrast, fails to provide such flexibility; a store can locate either at the neighborhood center, at the community center, or at the regional center; it can serve perhaps 5,000 people, 15,000 people, or 60,000 people. A store optimally sized to serve 10,000 people cannot be located at a consistent node level—or, if it is, it cannot be efficient. A firm may need to locate stores in some neighborhood centers and not others, causing people to go into other neighborhoods in some places.
Recognizing that grid-based road networks might not lend themselves to locations that were not situated on flat, featureless plains, designers introduced several variations. To conform to the contours of the land, Frederick Law Olmstead employed curving streets in many of his designs (e.g. Roland Park, Maryland). Permutations continued to evolve over the years, and the “loop” and “lollipop” designs became the standard in suburban settings

I think the idea of a particular network topology (grid vs. tree) depends a lot on the topography. Getting this right is important. The idea of laying something out in advance (Angel’s main point), so that property rights and development can occur on that lattice, seems a very good one.